This peer assessed assignment has two parts. In this project, I use the mtcars dataset.

• First, you will create a Shiny application and deploy it on Rstudio’s servers.

• Second, you will use Slidify or Rstudio Presenter to prepare a reproducible pitch presentation about your application.

The shiny app plots the relationship between different inputs from the mtcars dataset.

• Load data

• Summary data

##                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
## Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
## Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1

library(shiny)
shinyUI(fluidPage(
    
    # Application title
    titlePanel("Car Analysis"),
    
    sidebarPanel(
        
        selectInput("variable", "Variable:", 
                    c("Miles per gallon" = "mpg",
                      "Distance" = "disp",
                      "Cylinder" = "cyl"))
    ),
    
    mainPanel(
        h3(textOutput("caption")),

        plotOutput("carPlot")
    )
))

data('mtcars')

library(shiny)
library(plotly)
shinyServer(function(input, output) {
    
    formulaText <- reactive({
        paste("hp vs ", input$variable)
    })
    
    output$caption <- renderText({
        formulaText()
    })
    output$carPlot <- renderPlot({
       ggplot(mtcars,aes_string(x='hp',y=input$variable, col='hp')) + geom_point()
    })
    
})